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Jon Saad-FalconandClaude Opus 4.6
f1dfeb2567
Establishes OpenJarvis as a modular AI assistant backend with five composable pillars (Intelligence, Memory, Agents, Inference, Learning). Documents the architecture, supported backends, and phased development plan. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1.9 KiB
1.9 KiB
OpenJarvis
Your AI stack, your rules.
A modular, pluggable AI assistant backend. Compose your own stack across five pillars — Intelligence, Learning, Memory, Agents, and Inference — then swap any piece without touching the rest.
Status: Early Development — Interfaces are being defined. Not yet usable.
What is this?
OpenJarvis lets you build a personal AI assistant from composable parts:
- Intelligence — multi-model management with automatic routing (Qwen3, GPT OSS, Kimi-K2.5, Claude, GPT-5, Gemini)
- Memory — persistent, searchable storage with multiple backends (SQLite, FAISS, ColBERTv2, BM25, hybrid)
- Agents — pluggable reasoning and tool use (OpenClaw Pi agent, simple, orchestrator, custom)
- Inference — hardware-aware engine selection (vLLM, SGLang, Ollama, llama.cpp, MLX)
- Learning — router that improves over time (heuristic now, learned later)
Documentation
- VISION.md — Project vision, architecture, design principles, and detailed pillar descriptions
- ROADMAP.md — Phased development plan with deliverables and version milestones
Quick orientation
src/openjarvis/
├── core/ # Registry, types, config, event bus
├── intelligence/ # Model management, routing
├── memory/ # Storage backends (SQLite, FAISS, ColBERT, BM25, hybrid)
├── agents/ # Agent implementations + tool system
├── engine/ # Inference engine wrappers
├── learning/ # Router policy (placeholder)
└── cli/ # CLI entry points (jarvis ask, serve, model, memory)
Requirements
- Python 3.10+
- An inference backend: Ollama, vLLM, or llama.cpp
- Node.js 22+ (only if using OpenClaw agent)
License
TBD